An Efferent-Inspired Auditory Model Front-End for Speech Recognition
An Efferent-Inspired Auditory Model Front-End for Speech Recognition
复制标题
用于语音识别的传出听觉模型前端
DOI：
10.21437/interspeech.2011-13
复制
发表时间：
2011
影响因子：
1.8
通讯作者：
O. Ghitza
中科院分区：
文献类型：
--
作者：
Chia;James R. Glass;O. Ghitza
在本文中，我们研究了闭环听觉模型，并探索其作为语音识别特征表示的潜力。闭环表示由基于听觉的传出反馈机制组成，该机制调节滤波器组的工作点，从而使其能够动态适应不断变化的背景噪声。通过动态自适应，闭环表示能够补偿噪声对语音的影响，并在受到不同类型噪声污染时为语音生成一致的特征表示。我们的初步实验结果表明，与开环表示相比，传出启发反馈机制使闭环听觉模型能够持续提高单词识别精度，以应对连接数字识别任务中不匹配的训练和测试噪声条件。索引术语：传出、听觉模型、特征提取
In this paper, we investigate a closed-loop auditory model and explore its potential as a feature representation for speech recognition. The closed-loop representation consists of an auditory-based, efferent-inspired feedback mechanism that regulates the operating point of a filter bank, thus enabling it to dynamically adapt to changing background noise. With dynamic adaptation, the closed-loop representation demonstrates an ability to compensate for the effects of noise on speech, and generates a consistent feature representation for speech when contaminated by different kinds of noises. Our preliminary experimental results indicate that the efferent-inspired feedback mechanism enables the closed-loop auditory model to consistently improve word recognition accuracies, when compared with an open-loop representation, for mismatched training and test noise conditions in a connected digit recognition task. Index Terms: efferent, auditory model, feature extraction